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- PublicationInformation Synthesis for Answer Validation(2009)This report is about our participation in the Answer Validation Exercise (AVE2008). Our system casts the AVE task into a Recognizing Textual Entailment (RTE) problem and uses an existing RTE system to validate answers. Additional information from named-entity (NE) recognizer, question analysis component, and so on, is also considered as assistances to make the final decision. In all, we have submitted two runs, one run for English and the other for German. They have achieved f-measures of 0.64 and 0.61 respectively. Compared with our system last year, which purely depends on the output of the RTE system, the extra information does show its effectiveness.
- PublicationAnalysis-Ready Data from Hyperspectral Sensors—The Design of the EnMAP CARD4L-SR Data Product(2021)Today, the ground segments of the Landsat and Sentinel missions provide a wealth of well-calibrated, characterized datasets which are already orthorectified and corrected for atmospheric effects. Initiatives such as the CEOS Analysis Ready Data (ARD) propose and ensure guidelines and requirements so that such datasets can readily be used, and interoperability within and between missions is a given. With the increasing availability of data from operational and research-oriented spaceborne hyperspectral sensors such as EnMAP, DESIS and PRISMA, and in preparation for the upcoming global mapping missions CHIME and SBG, the provision of analysis ready hyperspectral data will also be of increasing interest. Within this article, the design of the EnMAP Level 2A Land product is illustrated, highlighting the necessary processing steps for CEOS Analysis Ready Data for Land (CARD4L) compliant data products. This includes an overview of the design of the metadata, quality layers and archiving workflows, the necessary processing chain (system correction, orthorectification and atmospheric correction), as well as the resulting challenges of this procedure. Thanks to this operational approach, the end user will be provided with ARD products including rich metadata and quality information, which can readily be integrated in analysis workflows, and combined with data from other sensors.